Search for dissertations about: "stochastic wave equation"

Showing result 1 - 5 of 10 swedish dissertations containing the words stochastic wave equation.

  1. 1. Approximating Stochastic Partial Differential Equations with Finite Elements: Computation and Analysis

    Author : Andreas Petersson; Chalmers University of Technology; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Lévy process; Lyapunov equation; white noise; finite element method; multilevel Monte Carlo; Monte Carlo; multiplicative noise; asymptotic mean square stability; stochastic heat equation; covariance operator; weak convergence; generalized Wiener process; numerical approximation; stochastic wave equation; Stochastic partial differential equations;

    Abstract : Stochastic partial differential equations (SPDE) must be approximated in space and time to allow for the simulation of their solutions. In this thesis fully discrete approximations of such equations are considered, with an emphasis on finite element methods combined with rational semigroup approximations. READ MORE

  2. 2. Topics in Simulation and Stochastic Analysis

    Author : Mikael Signahl; Matematisk statistik; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Mathematics; Matematik; stochastic heat equation; stochastic wave equation; error rates; truncated Levy process; discontinuities; optimal decay rate; digital communication system;

    Abstract : Paper A investigates how to simulate a differentiated mean in cases where interchanging differentiation and expectation is not allowed. Three approaches are available, finite differences (FD's), infinitesimal perturbation analysis (IPA) and the likelihood ratio score function (LRSF) method. READ MORE

  3. 3. The Finite Element Method for Fractional Order Viscoelasticity and the Stochastic Wave Equation

    Author : Fardin Saedpanah; Göteborgs universitet; Göteborgs universitet; Gothenburg University; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; finite element method; continuous Galerkin method; linear viscoelasticity; fractional calculus; fractional order viscoelasticity; weakly singular kernel; stability; a priori error estimate; a posteriori error estimate; stochastic wave equation; additive noise; Wiener process; strong convergence.; linear viscoelasticity;

    Abstract : This thesis can be considered as two parts. In the first part a hyperbolic type integro-differential equation with weakly singular kernel is considered, which is a model for dynamic fractional order viscoelasticity. In the second part, the finite element approximation of the linear stochastic wave equation is studied. READ MORE

  4. 4. On weak and strong convergence of numerical approximations of stochastic partial differential equations

    Author : Fredrik Lindgren; Göteborgs universitet; Göteborgs universitet; Gothenburg University; []
    Keywords : Additive noise; Cahn-Hilliard-Cook equation; Error estimate; Finite element; Hyperbolic equation; Parabolic equation; Rational approximation; Stochastic partial differential equation; Strong convergence; Truncation; Wiener process; Weak convergence; Weak convergence;

    Abstract : This thesis is concerned with numerical approximation of linear stochastic partial differential equations driven by additive noise. In the first part, we develop a framework for the analysis of weak convergence and within this framework we analyze the stochastic heat equation, the stochastic wave equation, and the linearized stochastic Cahn-Hilliard, or the linearized Cahn-Hilliard-Cook equation. READ MORE

  5. 5. Exponential integrators for stochastic partial differential equations

    Author : Rikard Anton; David Cohen; Christian Engström; Stig Larsson; Annika Lang; Umeå universitet; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; Stochastic partial differential equations; numerical methods; stochastic exponential integrator; strong convergence; trace formulas;

    Abstract : Stochastic partial differential equations (SPDEs) have during the past decades become an important tool for modeling systems which are influenced by randomness. Because of the complex nature of SPDEs, knowledge of efficient numerical methods with good convergence and geometric properties is of considerable importance. READ MORE